The Role of Data Analytics in Financial Decision-Making: Risk Management and Growth Opportunities for Bangladeshi Organizations
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Abstract
Data analytics knowledge is becoming increasingly vital to Bangladeshi enterprises, enabling them to make better financial decisions, proactively address risks, and set strategic objectives. Hence, this study emphasizes how data-driven tactics are becoming more widely used to make better decisions by offering greater insights into risk variables, market dynamics, and financial health. Organizations in Bangladesh are using a range of data sources, such as financial performance measurements, market trends, and risk assessment reports, to acquire actionable insights about their business operations and the financial environment. Businesses may more accurately assess risks, anticipate market moves, and analyze financial patterns when advanced analytics technologies like predictive models and strategic forecasting software are integrated. Complex tools such as predictive models and forecasting software are very effective in risk assessment, market forecasting, and trend analysis. The findings of the study from such industries as manufacturing, retail, and finance, Fortuna Shoes, Bikroy, and Daraz case studies demonstrated that the organizations utilize real-time analytics to maximally align their operations with consumer behavior. Also, in the same aspect, programs such as Skills Development Program by BRAC can yield socially beneficial results as well. Having all the challenges, the increased use of analytics brings Bangladeshi organizations to a position where they have made critical decisions to perform even better given the complex nature of the economic environment.
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Ahmed, R. (2022, February 17). Decision-making processes: Bangladeshi large enterprises’ transition to cloud ERP systems. figshare. https://bridges.monash.edu/articles/thesis/Decision-Making_Processes_Bangladeshi_Large_Enterprises_Transition_to_Cloud_ERP_Systems/19095308?file=33934235
Ahsan, S. (2020, February 12). Endless possibilities with big data analytics in Bangladesh. The Business Standard. https://www.tbsnews.net/tech/endless-possibilities-big-data-analytics-bangladesh-44041
Aziz, F. (2023, May 25). Data analytics impacts in the field of accounting. World Journal of Advanced Research and Reviews. https://wjarr.com/content/data-analytics-impacts-field-accounting
Aziz, F., Haque, T. A., Hossain, M. B., Rahman, A., & Siam, S. A. (2023, October 19). Customer Behavior Analysis Through Data Analytics in the Bangladeshi Retail Industry. ResearchGate. https://www.researchgate.net/publication/374813909_Customer_Behavior_Analysis_Through_Data_Analytics_in_the_Bangladeshi_Retail_Industry
Barney, J. B. (2001). Resource-based theories of competitive advantage: A ten-year retrospective on the resource-based view. Journal of Management, 27(6), 643-650. https://doi.org/10.1177/014920630102700602
Chen, H., Chiang, R. H., & Storey, V. C. (2012). Business intelligence and analytics: From big data to big impact. MIS quarterly, 1165-1188. Doi: https://doi.org/10.2307/41703503
Choudhury, M. K. (2017, April 12). Business data analytics in Bangladesh: No more trying to find a needle in the haystack. LinkedIn. https://www.linkedin.com/pulse/business-data-analytics-bangladesh-more-trying-find-needle-choudhury/
Chowdhury, F. K. (2023, March 22). Data-driven strategy in the promised ‘Smart Bangladesh’. The Business Standard. https://www.tbsnews.net/thoughts/data-driven-strategy-promised-smart-bangladesh-591918
Davenport, T. H., Harris, J. G., Jones, G. L., Lemon, K. N., Norton, D., & McCallister, M. B. (2007). The dark side of customer analytics. Harvard Business Review. https://hbr.org/2007/05/the-dark-side-of-customer-analytics
Davenport, T. H. (2013, December 1). Analytics 3.0. Harvard Business Review. https://hbr.org/2013/12/analytics-30
Faruk, M. (2019, June 20). Factors affecting the Adoption Intention of Big Data Analytics: An Exploratory Analysis in Bangladeshi Context. https://www.iba-ju.edu.bd/volume-20-article-2/
Fiedler, F. E. (1993). The contingency model: New directions for leadership utilization. In Matteson and Ivancevich (Eds.), Management and Organizational Behavior Classics.
Jorion, P. (2007) Value at Risk: The New Benchmark for Managing Financial Risk. Vol. 3, McGraw-Hill, New York. https://books.google.co.in/books?id=nnblKhI7KP8C&printsec=frontcover&redir_esc=y#v=onepage&q&f=false
Kabadurmus, O., & Özemre, M.
(2020, February 4). A big data analytics based methodology for strategic decision-making. ResearchGate. https://www.researchgate.net/publication/341680958_A_big_data_analytics_based_methodology_for_strategic_decision_making
Latif, A., Fairdous, R., Akhtar, R., & Ambreen, M. (2023, June 20). Exploring the impact of big data analytics on organizational decision-making and performance:
Insights from Pakistan's industrial
sector. iRASD Journals. Doi: http://dx.doi.org/10.52131/pjhss.2023.1102.0475
Pal, S. (2023, November 15). Business data & analytics for sustainable financing. The Financial Express. https://today.thefinancialexpress.com.bd/views-opinion/business-data-analytics-for-sustainable-financing-1699973091
Rahman, M. S., Hasan, M. J., Hossain Khan, M. S., & Jahan, I. (2023, February). Antecedents and effect of creative accounting practices on organizational outcomes: Evidence from Bangladesh. ScienceDirect. https://www.sciencedirect.com/science/article/pii/S2405844023009660
Ramrathan, D., & Sibanda, M. (2014, February 2). Impact of analytics in financial decision making: Evidence F. Economics and Finance Research IDEAS/RePEc. https://ideas.repec.org/a/dug/actaec/y2014i5p124-135.html
RIB Software. (2024, June 6). The importance of data driven decision making in business. RIB Software. https://www.rib-software.com/en/blogs/data-driven-decision-making-in-businesses
Sarker, I. H. (2021, July 12). Data science and analytics: An overview from data-driven smart computing, decision-making and applications perspective. SpringerLink. https://link.springer.com/article/10.1007/s42979-021-00765-8
Shahnawaz, S. (2019, August 6). Analytics, big data and financial governance. The Financial Express. https://www.thefinancialexpress.com.bd/views/analytics-big-data-and-financial-governance.
Shmueli, G., & Jr., K. C. (2016). Practical time series forecasting with R: A hands-on guide [2nd edition]. Axelrod Schnall Publishers. https://books.google.co.in/books/about/Practical_Time_Series_Forecasting_with_R.html?id=DKIYvgAACAAJ&redir_esc=y
Taher, S. A., & Uddin, M. K. (2018, June 27). Use of big data in financial sector of Bangladesh – A review. EconStor. https://www.econstor.eu/handle/10419/190348
Von Neumann, J. and Morgenstern, O. (1944) Theory of Games and Economic Behavior. Princeton University Press, Princeton. https://press.princeton.edu/books/paperback/9780691130613/theory-of-games-and-economic-behavior?srsltid=AfmBOoqphTnGQWuAEHnaOniL9skrZcbqZxX_-tMrXVFEqixod0v3ZBeD
Akramovna, I. N., Takhirjonovna, A. S., & Kholmatjanovich, M. B. (2019). Risk Management and Insurance. In International Journal of Innovative Technology and Exploring Engineering (Vol. 8, Issue 12, pp. 5429–5432). Doi: https://doi.org/10.35940/ijitee.g5722.1081219
Prokopenko, O., Kholod, B., Pavlova, V., Niziaieva, V., Shtepa, O., & Orlova, V. (2019). Risk Management Culture as a Systematic Method for Ensuring Safety Development. In International Journal of Recent Technology and Engineering (IJRTE) (Vol. 8, Issue 4, pp. 8652–8657). Doi: https://doi.org/10.35940/ijrte.d8653.118419
Nayak, M. (2020). A Method for Effective IT Project Risk Management. In International Journal of Engineering and Advanced Technology (Vol. 9, Issue 3, pp. 3480–3484). Doi: https://doi.org/10.35940/ijeat.c5629.029320
Priya, Ms. K., & Lal, Dr. P. (2024). Awareness and Competence in Financial Literacy and Planning: The Financial Journey of Working Women. In International Journal of Management and Humanities (Vol. 10, Issue 8, pp. 17–22). Doi: https://doi.org/10.35940/ijmh.h1700.10080424